In the first weeks of 2026, the conversation around artificial intelligence feels like the weather: everyone notices it, few agree on the forecast, and most executives pretend they have an umbrella when, in fact, they don’t.
Generative AI—systems that draft reports, write code, summarize policy, and synthesize voices—is no longer a novelty. It’s woven into back-office automation, customer engagement platforms, and strategic planning tools. But tucked inside the rosy productivity headlines is a question that has migrated from the margins to the mainstream: what happens if these systems become not just useful but agentic—capable of autonomous action, strategy, and adaptation at scale?
For leaders in the Gulf Cooperation Council’s banking and regulatory communities, this isn’t an abstract musing. It’s a real planning problem with timelines measured in months and quarters, not decades.
We are at a hinge point because generative models are no longer just assistants. They are becoming operators. They connect to real systems—cloud environments, application programming interfaces, trading platforms, workflow engines—with increasing autonomy. They can:
This doesn’t require science fiction “sentience.” It requires careful engineering and, crucially, business incentives that reward rapid adoption without parallel investment in assurance.
Three Plausible Near-Term Scenarios
Instead of asking “Will we have AGI in 2026?”—a question with answers that vary by definition—it is more useful to ask: what are the realistic capabilities and risks we will need to manage in 2026?
Imagine a system that can independently draft contracts, negotiate terms via email, generate compliance filings, or optimise transaction workflows. Individually, these sound like efficiency gains. Combined, they form systems of delegated authority—digital actors with influence on financial operations, supply chains, and customer interactions.
Political risk isn’t tangential for banks: market confidence, regulatory legitimacy, and social stability are fragile. If generative AI can produce billions of personalized persuasive messages or automated lobbying campaigns, trust in public discourse—and in institutions that depend on it—erodes. This is not speculative noise; it is a systemic stressor.
AI that can generate plausible biological protocols, innovative code exploits, or narrative campaigns tailored to exploit social fault lines lowers the skill barriers for harm. In cybersecurity and biosecurity alike, misuse does not require genius; it requires access to tools that translate intent into effective action. The more capable these tools become, the more accessible the harms.
In the Gulf, many institutions are rightly focused on digital transformation, cloud migration, and AI-augmented services. But the upside of productivity cannot be separated from the risk of delegated uncertainty:
1. Treat AI Capability Like Critical Infrastructure
Just as banks approach cyber risk with layered defences, so too must they treat advanced AI with rigorous pre-deployment testing, independent evaluation, and continuous monitoring.
2. Regulate Capability, Not Just Use Cases
An AI system that can autonomously replicate tasks or circumvent safety guardrails is inherently higher-risk regardless of its labelled use case. Regulatory regimes should categorise and control based on systemic capabilities, not business descriptions.
3. Demand Accountability and Provenance
Content authentication, traceable model decision-logging, and identity management are not optional. These capabilities must be integrated into any system that influences financial, legal, or policy outcomes.
4. Align Incentives with Safety Outcomes
Liability frameworks, audit obligations, and incident reporting must evolve to reflect the speed and impact of autonomous systems. A traditional compliance checklist cannot keep up with a digital agent executing multi-stage tasks overnight.
5. Enforce Human-Centric Controls by Default
“Human-in-the-loop” must be more than branding; it must be embedded into architectural design:
The real risk of AI is not that it will wake up and decide we are obsolete. The real risk is that it will work, very effectively, on behalf of interests we don’t control; on timelines we don’t supervise; with consequences we neither predicted nor prepared for.
GCC banking and regulatory leaders have a unique opportunity—not just to adopt AI, but to shape the norms, rules, and expectations that will determine whether this technology serves stability or undermines it. The question is not whether 2026 will be transformative—it almost certainly will. The question is whether that transformation will be governed with foresight or remedied with regret.
If you want, I can tailor this further for LinkedIn Pulse publication, adding a compelling opener, a succinct executive summary, and a set of clear action bullets that resonate with C-suite risk officers and regulators in the Gulf context.
